In the early morning hours of 1 August 2015, as it waited for its next ride on a Philly park bench, unknown assailants destroyed hitchBOT. Arms torn from its body, legs broken, gutted of its electronics, it was left discarded in a park, minus its smiley-face LED head. Around the world headlines announced the death of a much-loved robot, children and adults shed tears, haters hated on Philadelphia, cartoonists and musicians paid tribute, journalists wrote obituaries and the publicly minded rallied to support a rebuild. The authors share the story of the life and times of their creation, hitchBOT the hitchhiking robot.

In 2014, a chatty but immobile robot called hitchBOT set out to hitchhike across Canada. It similarly made its way across Germany and the Netherlands, and had begun a trip across the USA when it was destroyed by vandals. In this work, we analyze the emotions and sentiments associated with words in tweets posted before and after hitchBOT's destruction to answer two questions: Were there any differences in the emotions expressed across the different countries visited by hitchBOT? And how did the public react to the demise of hitch-BOT? Our analyses indicate that while there were few cross-cultural differences in sentiment towards hitchBOT, there was a significant negative emotional reaction to its destruction, suggesting that people had formed an emotional connection with hitchBOT and perceived its destruction as morally wrong. We discuss potential implications of anthropomorphism and emotional attachment to robots from the perspective of robot ethics.

This paper describes a new research project that aims to develop an autonomous and responsive social robot designed to help children cope with painful procedures in hospital emergency departments. While this is an application domain where psychological interventions have been previously demonstrated to be effective at reducing pain and distress using a variety of devices and techniques, in recent years, social robots have been trialled in this area with promising initial results. However, until now, the social robots that have been tested have generally been teleoperated, which has limited their flexibility and robustness, as well as the potential to offer personalized, adaptive procedural support. Using co-design techniques, this project plans to define and validate the necessary robot behaviour together with participant groups that include children, parents and caregivers, and healthcare professionals. Identified behaviours will be deployed on a robot platform, incorporating AI reasoning techniques that will enable the robot to adapt autonomously to the child's behaviour. The final robot system will be evaluated through a two-site clinical trial. Throughout the project, we will also monitor and analyse the ethical and social implications of robotics and AI in paediatric healthcare.

We propose an alternative evaluation metric to Word Error Rate (WER) for the decision audit task of meeting recordings, which exemplifies how to evaluate speech recognition within a legitimate application context. Using machine learning on an initial seed of human-subject experimental data, our alternative metric handily outperforms WER, which correlates very poorly with human subjects' success in finding decisions given ASR transcripts with a range of WERs.

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